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, Atmospheric and Oceanic Sciences, Geosciences, Computational Science and Engineering, or a related area is required.The position will involve developing models and algorithms for the evolution of inorganic
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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developing novel methods and algorithms for applications in the Engineering Design domain; demonstrating a commitment to deliver results; working on research proposals; and working in a team environment. Job
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. This project will develop new AI algorithms and apply these methods to the agriculture sector in Ireland, focusing on dairy farming. Dairy farming is a very energy intensive form of farming. In order to
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This project project will develop strategies for programmable DNA origami tiling and opto-mechanical metasurfaces that combine self-assembly with precise optical functionality. The work will explore how DNA
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develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias detection tools, building fairness-aware algorithms, and contributing to practical guidelines
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations. The postdoctoral researcher will be supervised by Jean-Christophe Mourrat, in